It was recently demonstrated [J. Electron. Imaging, 25(2), 2016] that one can perform fast non-local means (NLM) denoising of one-dimensional signals using a method called lifting. The cost of lifting is independent of the patch length, which dramatically reduces the run-time for large patches. Unfortunately, it is difficult to directly extend lifting for non-local means denoising of images. To bypass this, the authors proposed a separable approximation in which the image rows and columns are filtered using lifting. The overall algorithm is significantly faster than NLM, and the results are comparable in terms of PSNR. However, the separable processing often produces vertical and horizontal stripes in the image. This problem was previously addressed by using a bilateral filter-based post-smoothing, which was effective in removing some of the stripes. In this letter, we demonstrate that stripes can be mitigated in the first place simply by involving the neighboring rows (or columns) in the filtering. In other words, we use a two-dimensional search (similar to NLM), while still using one-dimensional patches (as in the previous proposal). The novelty is in the observation that one can use lifting for performing two-dimensional searches. The proposed approach produces artifact-free images, whose quality and PSNR are comparable to NLM, while being significantly faster.
Inner-ear Augmented Metal Artifact Reduction with Simulation-based 3D Generative Adversarial Networks
Université Côte d’Azur（蔚蓝海岸大学）；Inria Sophia Antipolis Méditerranée（法国国家信息与自动化研究所索菲亚·安蒂波利斯-地中海研究中心）；Head and Neck University Institute, Nice University Hospital（尼斯大学医院头颈大学研究所）；Department of Radiology, Nice University Hospital（尼斯大学医院放射科）；Oticon Medical（奥迪康医疗公司）
RSTAR4D: Rotational Streak Artifact Reduction in 4D CBCT using a Separable 4D CNN
School of Biomedical Engineering, Shanghai Jiao Tong University（上海交通大学生物医学工程学院）；Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine（上海交通大学医学院附属胸科医院）；Jiangsu First-Imaging Tech.（江苏首影科技有限公司）；Research Center of Augmented Intelligence, Zhejiang Lab（之江实验室增强智能研究中心）；School of Computer Science and Engineering, Southeast University（东南大学计算机科学与工程学院）
Multi-domain CT Metal Artifacts Reduction Using Partial Convolution Based Inpainting
Skolkovo Institute of Science and Technology（斯科尔科沃科学技术研究院）；Kharkevich Institute for Information Transmission Problems（哈尔克维奇信息传输问题研究所）；Moscow Institute of Physics and Technology（莫斯科物理技术学院）；N. N. Burdenko National Medical Research Center of Neurosurgery（N.N.布尔坚科国家神经外科医学研究中心）；Lomonosov Moscow State University（罗蒙诺索夫莫斯科国立大学）；Moscow Gamma Knife Center（莫斯科伽马刀中心）
GraphMAR: Geometry-Aware Graph Learning Framework for Spatially Adaptive CT Metal Artifact Reduction
Shanghai Key Lab of Intelligent Information Processing, College of Computer Science and Artificial Intelligence, Fudan University（上海智能信息处理关键实验室，计算机科学与人工智能学院，复旦大学）；Institute of Science and Technology for Brain-inspired Intelligence, Fudan University（脑启发式智能科学技术研究院，复旦大学）；College of Computer Science and Technology, Qingdao University（计算机科学与技术学院，青岛大学）；Department of Oral Maxillofacial Head and Neck Oncology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine（口腔颌面头颈肿瘤科，上海第九人民医院，上海交通大学医学院）；School of Cyber Science and Engineering, Sichuan University（网络科学与工程学院，四川大学）
"One-Shot" Reduction of Additive Artifacts in Medical Images
National Tsing Hua University（清华大学）；University of Notre Dame（圣母大学）；Guangdong Provincial People’s Hospital（广东省人民医院）；Guangdong Acadamic of Medical Science（广东医学科学院）
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
University of Rochester（罗切斯特大学）；University of Maryland, College Park（马里兰大学帕克分校）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；Peng Cheng Laboratory（鹏城实验室）
Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
University of Rochester（罗切斯特大学）；University of Maryland, College Park（马里兰大学帕克分校）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）
Annealed Score-Based Diffusion Model for MR Motion Artifact Reduction
Korea Advanced Institute of Science and Technology (KAIST)（韩国科学技术院）；Chungnam National University Hospital（忠南大学医院）；Chungnam National University College of Medicine（忠南大学医学院）
VoxelSynth3D: Interpretable Volumetric Image-Domain Metal Artifact Reduction with a Paired Synthetic CLINIC Benchmark
University of Massachusetts at Amherst（马萨诸塞大学阿默斯特分校）；New York University Abu Dhabi (NYUAD)（纽约大学阿布扎比分校）；Indian Institute of Technology Delhi Abu Dhabi（印度理工学院德里分校阿布扎比校区）；NYUAD Research Institute（纽约大学阿布扎比分校研究院）
U-DuDoNet: Unpaired dual-domain network for CT metal artifact reduction
Z 2 Sky Technologies Inc.（Z 2 天空科技公司）；Beijing University of Posts and Telecommunications（北京邮电大学）；Johns Hopkins University（约翰斯·霍普金斯大学）；Suzhou Institute for Advance Research, University of Science and Technology of China（中国科学技术大学苏州研究院）；Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS（中国科学院计算技术研究所中国科学院智能信息处理重点实验室）
Balancing Efficiency and Restoration: Lightweight Mamba-Based Model for CT Metal Artifact Reduction
New York University（纽约大学）；BaiyunPort（白云港）；University of Technology Sydney（悉尼科技大学）；Sanda University（上海杉达学院）；Shan Dong Xiehe College（山东协和学院）；Tsinghua University（清华大学）；Gannan Normal University（赣南师范大学）；Southern Medical University（南方医科大学）；Shenzhen Research Institute of Big Data（深圳市大数据研究院）
Projection Inpainting Using Partial Convolution for Metal Artifact Reduction
Friedrich-Alexander Universität Erlangen-Nürnberg（弗里德里希-亚历山大大学埃尔朗根-纽伦堡分校）；Erlangen Graduate School in Advanced Optical Technologies (SAOT)（埃尔兰根先进光学技术研究生院（SAOT））
DuDoNet: Dual Domain Network for CT Metal Artifact Reduction
University of Maryland, College Park（马里兰大学帕克分校）；University of Rochester（罗切斯特大学）；Princeton University（普林斯顿大学）；Z2W Corporation（Z2W公司）；Chinese Academy of Sciences（中国科学院）；Peng Cheng Laboratory（鹏城实验室）
Physically-Grounded Manifold Projection Model for Generalizable Metal Artifact Reduction in Dental CBCT
School of Cyberspace, Hangzhou Dianzi University（电子科技大学信息学院）；Innovation Center for Electronic Design Automation Technology, Hangzhou Dianzi University（电子科技大学电子设计自动化创新中心）；Hangzhou Geriatric Stomatology Hospital, Hangzhou Dental Hospital Group（杭州老年口腔医院，杭州口腔医院集团）；School of Computing and Mathematical Sciences, University of Leicester（莱斯特大学计算与数学科学学院）
Encoding Metal Mask Projection for Metal Artifact Reduction in Computed Tomography
Z 2 Sky Technologies Inc.（Z 2 Sky科技公司）；Adobe（奥多比公司）；University of Rochester（罗切斯特大学）；Beijing United Family Hospital（北京和睦家医院）；Peking Union Medical College Hospital（北京协和医院）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；Peng Cheng Laboratory（鹏城实验室）
Unlocking the Potential of Early Epochs: Uncertainty-aware CT Metal Artifact Reduction
JancsiTech（扬希科技）；Shenzhen Institute of Advanced Technology, Chinese Academy of Science（中国科学院深圳先进技术研究院）；University of Science and Technology of China（中国科学技术大学）
Automated Segmentation of Hip and Thigh Muscles in Metal Artifact-Contaminated CT using Convolutional Neural Network-Enhanced Normalized Metal Artifact Reduction
Nara Institute of Science and Technology（奈良先端科学技术大学院大学）；Osaka University（大阪大学）
Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction
University of Rochester（罗切斯特大学）；University of Maryland, College Park（马里兰大学帕克分校）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；Carestream Health, Inc.（锐珂医疗公司）
AS-Mamba: Asymmetric Self-Guided Mamba Decoupled Iterative Network for Metal Artifact Reduction
School of Information Engineering, Nanchang University（信息工程学院，南昌大学）；School of Mathematics and Computer Sciences, Nanchang University（数学与计算机科学学院，南昌大学）；The First Affiliated Hospital, Jiangxi Medical College, Nanchang University（江西医学院第一附属医院，南昌大学）；LargeV Instrument Corp., Ltd.（大维仪器有限公司）
A$^3$DSegNet: Anatomy-aware artifact disentanglement and segmentation network for unpaired segmentation, artifact reduction, and modality translation
Z 2 Sky Technologies Inc.（Z 2 天工科技公司）；University of Rochester（罗切斯特大学）；Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS（中国科学院计算技术研究所 中国科学院智能信息处理重点实验室）；University of Science and Technology of China（中国科学技术大学）；Suzhou Institute for Advance Research, University of Science and Technology of China（中国科学技术大学苏州高等研究院）
